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The authors compare current machine learning algorithms with a new Explainable AI algorithm that produces a human-comprehensible decision tree alongside predictions.

The authors looked at different ways to build computational resources that would analyze shooting form for basketball players.

Here, the authors investigated the integration of large language models (LLMs) with drug target affinity predictors (DTAPs) to improve drug repurposing, demonstrating a significant increase in prediction accuracy, particularly with GPT-4, for psychotropic drugs and the sigma-1 receptor. This novel approach offers to potentially accelerate and reduce the cost of drug discovery by efficiently identifying new therapeutic uses for existing drugs.

The authors studied the chemoreception of moon jellyfish in response to food, and developed an AI tool to identify track and quantify the pulsation of swimming jellyfish.

Recent advances in generative AI have made it increasingly hard to distinguish real images from AI-generated ones. Traditional detection models using CNNs or U-net architectures lack precision because they overlook key spatial and frequency domain details. This study introduced a hybrid model combining Convolutional Neural Networks (CNN) with Fast Fourier Transform (FFT) to better capture subtle edge and texture patterns.

The authors train a neural network to detect text-based emotions including joy, sadness, anger, fear, love, and surprise.

Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.

Authors examine the effectiveness of Large Language Models (LLMs) like BERT, MathBERT, and OpenAI GPT-3.5 in assisting middle school students with math word problems, particularly following the decline in math performance post-COVID-19.

In this article, the authors propose an effective, environmentally-friendly method of producing conductive ink using expired waste oil, polystyrene, and graphene.

The authors employ computational protein design to identify a mini-protein with the potential to enhance binding of the tight junction protein, claudin-5, at the blood-blood barrier with therapeutic potential for neurodegenerative diseases.